Xi Jessie Yang

Xi Jessie Yang is an Associate Professor in Industrial and Operations Engineering and Robotics at the University of Michigan. Her research focuses on human-autonomy interaction, human factors in high-risk industries, and user experience design. She leads the Interaction & Collaboration Research Lab (ICRL), which develops design solutions for effective human-robot collaboration.

Her research spans critical areas including trust dynamics in automation, explainable AI, and safety-critical systems. Key themes include understanding how users perceive and interact with autonomous systems in transportation, healthcare, and robotics contexts. Recent work emphasizes real-time trust modeling, adaptive human-robot teamwork, and mitigating risks through transparent AI interfaces.

Publications highlight advancements in automated driving systems, pharmacy automation trust calibration, and social navigation for robots. Her team employs mixed-methods approaches combining experimental studies, computational models, and machine learning to address challenges in human-AI collaboration.

Notable contributions include the TIP model for trust inference in multi-agent systems, context-aware trust profiles for automated vehicles, and frameworks for explaining AI decisions to non-experts. Her work bridges engineering, cognitive science, and social sciences to create human-centered technologies.